Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World

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This paper, published in 1950, received 390 indexed citations. Written by Sharon K. Parker and Gudela Grote covering the research area of Industrial and Manufacturing Engineering, Sociology and Political Science and Social Psychology. It is primarily cited by scholars working on Social Psychology (116 citations), Sociology and Political Science (105 citations) and Organizational Behavior and Human Resource Management (97 citations). Published in Applied Psychology.

Countries where authors are citing Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World

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This map shows the geographic impact of Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World more than expected).

Fields of papers citing Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1111/apps.12241.

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